The world’s forcibly displaced population hit its record high in 2017. Globally, at the end of 2017, the global refugee population increased by 2.9 million. By the end of the year, 68.5 million individuals were forcibly displaced worldwide as a result of persecution conflict, or generalized violence (https://www.unhcr.org/5b27be547.pdf). Despite the increase in demand for refugee admission and assistance, the United States specifically has taken a drastic turn away from supporting refugees. The number of refugees admitted to the United States has dropped from a recent high of 84,994 in FY 2016 to 22,874 in FY 2018 - the lowest in 40 years since 1977. The current ceiling for refugee admission has also dropped to 45,000, the lowest in the history of the current US resettlement program. Coming at a time when global numbers of refugees have reached record highs, the ratio of refugees admitted to the United States to the number of refugees worldwide has never been lower. For the first time, the US policy towards refugee admission is moving decisively against the trend of the total number of refugees worldwide (https://www.cgdev.org/blog/reflecting-world-refugee-day-trends-and-consequences-us-refugee-policy). The recent years thus mark a significant shift in refugee resettlement in the US, as a result, this report will be examining the refugee admission trend in the US over the past 10 years (2009-2018).
According to the UNHCR, refugees are defined as those who have been forced to leave their country due to violence, war, or persecution based on their race, religion, nationality, political opinion or particular social group.
Process of refugee resettlement:
The process of refugee resettlement to the U.S. is a lengthy and thorough process that takes approximately two years and involves numerous U.S. governmental agencies
Refugees do not choose the country in which they would like to live. UNHCR, the UN Refugee Agency identifies the most vulnerable refugees for resettlement and then makes recommendations to select countries.
Under the Refugee Act of 1980, the president sets an annual ceiling for refugee admissions in consultation with Congress. The annual ceiling has varied over the years, from a high of 231,700 in FY 1980 to a prior low of 67,000 in FY 1986. Amid a large exodus of Syrinas from their war-torn country, President Obama raised the refugee ceiling for FY 2016 to 110,000. After taking office, Trump reduced the FY 2017 cap to 50,000, and for FY 2018 set one at a historic low of 45,000. Far fewer refugees, 22,874, were actually resettled in FY 2018.
There are currently 25.9 million refugees in the world, indicating the dramatic growth in refugees over the past decade. This led us to question what the refugee resettlement trend has been for the past decade, and delve deeper than just the changes in the numbers of refugees. In order to better visualize the trend of refugee resettlement to the US, this report will be specifically focusing on the top 5 countries (Burma, Iraq, Somalia, Bhutan, Democratic Republic of the Congo) with the highest refugee resettlement population in the US, which accounted for 60.9% of the total refugee arrivals in the US (https://data.newamericaneconomy.org/en/refugee-resettlement-us/).
We are interested in answering the following questions to gain a better understanding of the refugee resettlements in the United States:
What insights can we gain from geographical visualization of refugee settlement patterns in the US over the 10 years? Why might some states have larger refugee settlements than others?
We first collected data from RPC (Refugee Processing Center), that provides refugee arrival information by state and nationality, by destination and nationality, by nationality and religion, and by demographic profile.
We can select the time frame, nationality. Since the RPC website does not allow for faceting by year, we had to download the files year by year, and clean the data into the format we want for data analysis.
clean_arrival to clean the Excel files for all refugee resettlements for each state.clean_demographics to clean the Excel files for demographic information for refugees from specific countries (namely Bhutan, Burma, DRC, Iraq, and Somalia).combine_files, to combine each year’s Excel file into one.After cleaning the data, we have six ‘.csv’ files that can be found here.
all_arrivals.csv: The total number of refugee resettlements to each of the 50 states in the US from 2009-2018. All raw files to make this file can be found here.| State | Cases | Inds | Year |
|---|---|---|---|
| California | 5524 | 11512 | 2009 |
| Texas | 3638 | 8826 | 2009 |
| New York | 2013 | 5003 | 2009 |
| Arizona | 1952 | 4543 | 2009 |
| Florida | 1834 | 4196 | 2009 |
| Michigan | 1602 | 3460 | 2009 |
age_group.csv:| Age.Group | Male | Female | Total | country | Year |
|---|---|---|---|---|---|
| Under 14 | 1559 | 1627 | 3186 | Bhutan | 2009 |
| Age 14 to 20 | 1258 | 1310 | 2568 | Bhutan | 2009 |
| Age 21 to 30 | 1823 | 1927 | 3750 | Bhutan | 2009 |
| Age 31 to 40 | 1110 | 1124 | 2234 | Bhutan | 2009 |
| Age 41 to 50 | 726 | 737 | 1463 | Bhutan | 2009 |
| Age 51 to 64 | 583 | 626 | 1209 | Bhutan | 2009 |
education.csv:| Education | Male | Female | Total | country | Year |
|---|---|---|---|---|---|
| Bio Data not Complete | 2657 | 1846 | 4503 | Bhutan | 2009 |
| Graduate School | 21 | 144 | 165 | Bhutan | 2009 |
| Intermediate | 509 | 496 | 1005 | Bhutan | 2009 |
| Kindergarten | 123 | 127 | 250 | Bhutan | 2009 |
| NONE | 100 | 42 | 142 | Bhutan | 2009 |
| Pre-University | 1 | 1 | 2 | Bhutan | 2009 |
ethnicity.csv:| Ethnicity | Male | Female | Total | country | Year |
|---|---|---|---|---|---|
| Lhotsampa | 7373 | 7677 | 15050 | Bhutan | 2009 |
| Other | 12 | 15 | 27 | Bhutan | 2009 |
| Lhotsampa | 5842 | 5881 | 11723 | Bhutan | 2010 |
| Other | 3 | 3 | 6 | Bhutan | 2010 |
| Lhotsampa | 7314 | 7410 | 14724 | Bhutan | 2011 |
| Other | 4 | 7 | 11 | Bhutan | 2011 |
native_language.csv:| Native.Language | Male | Female | Total | country | Year |
|---|---|---|---|---|---|
| Bio Data not Complete | 3 | 4 | 7 | Bhutan | 2009 |
| Dzongka | 0 | 1 | 1 | Bhutan | 2009 |
| English | 2 | 1 | 3 | Bhutan | 2009 |
| Hindi | 1 | 0 | 1 | Bhutan | 2009 |
| Marathi | 1 | 0 | 1 | Bhutan | 2009 |
| Napoletano-Calabrese | 0 | 1 | 1 | Bhutan | 2009 |
religion.csv:| Religion | Male | Female | Total | country | Year |
|---|---|---|---|---|---|
| Buddhist | 748 | 853 | 1601 | Bhutan | 2009 |
| Christian | 534 | 518 | 1052 | Bhutan | 2009 |
| Hindu | 5798 | 5993 | 11791 | Bhutan | 2009 |
| Kirat | 305 | 328 | 633 | Bhutan | 2009 |
| Buddhist | 925 | 910 | 1835 | Bhutan | 2010 |
| Christian | 468 | 453 | 921 | Bhutan | 2010 |
TODO: WRITE STUFF
The datasets from RPC (Refugee Processing Center) did not contain any missing values. However, we also noticed that our data contained a single row called “Unknown State”. Since this would not be plotted in our maps, we decided that it would be better to remove the data. Additionally, when we converted the State column to factors, there were 56. The extra 6 states are:
We removed these rows since we are just curious about the fifty states.
In Education data, we observed the proportion of missing data compared to the total data. For example, Bhutan has more than 30% of missing data in education.
Given our datasets, it is apparent that the temporal patterns of our data are of great importance to our analysis. As a result, to provide a general view of the overall change in resettlement population from 2009 to 2018, we chose to use a time series graph.
In this graph, we have the years we are looking at on the x-axis and the population count on the y-axis. The green line indicates the ceiling set by the U.S. government on the maximum of refugees that can be admitted. The red line indicates the actual number of individuals admitted. We hypothesize that the change in the refugee admission ceiling and the actual refugee resettlement population are correlated with:
Looking at the general trend of change in refugee admission ceiling, the two timepoints that stand out the most are 2015 and 2016. * In 2015, the refugee admission ceiling increased drastically from 70,000 to a record high of 85,000 in 2016 under President Obama’s administration. * In 2016, however, the refugee admission ceiling decreased drastically from 85,000 to a record low of 45,000 in 2018 under President Trump’s administration and has continued to decrease.
Looking at the general trend of change in the actual refugee resettlement population, we can see that the population decreased from 79,943 in 2009 to a low of 51,458 in 2011, when President Obama was re-elected. However, the resettlement population increased from 51,458 in 2011 to a record high of 96,874 in 2016, and decreased drastically from 96,874 in 2016 to a record low of 22,847 in 2018 under President Trump’s administration.
We take a closer look at the top 5 countries that have refugees resettled in the USA (https://data.newamericaneconomy.org/en/refugee-resettlement-us/).
The top 5 religions in the world are: Christianity, Islam, Hinduism, Buddhism, Sikhism (https://thecountriesof.com/top-5-largest-religions-in-the-world/). In Iraq, they separate the Muslim population into three categories: Muslim, Muslim Shiite, and Muslim Suni. For the purposes of this analysis, we will combine them as one.
DRC and Somalia have the highest proportions of refugees who are under 14.
TODO: WRITE STUFF